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Showing 181 - 200 results of 906 for search '(((( data modeling algorithm ) OR ( problem using algorithm ))) OR ( element method algorithm ))*', query time: 0.13s Refine Results
  1. 181
    Cyberbullying Detection Model for Arabic Text Using Deep Learning

    Cyberbullying Detection Model for Arabic Text Using Deep Learning by Albayari, Reem

    Published 2023
    “…As a result of the models’ evaluation, a hybrid DL model is proposed that combines the best characteristics of the baseline models CNN, BLSTM and GRU for identifying cyberbullying. …”
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  2. 182
    Neural Networks as a Convex Problem

    Neural Networks as a Convex Problem by Khalil, Baha

    Published 2016
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  3. 183
    Transformations for Variants of the Travelling Salesman Problem and Applications

    Transformations for Variants of the Travelling Salesman Problem and Applications by Assaf, Mustafa Jamil

    Published 2017
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  4. 184
    Fault-Tolerant Network Topologies for Datacenters

    Fault-Tolerant Network Topologies for Datacenters by Attia, Heba Mahmoud Helal

    Published 2017
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  5. 185
    A Comparative study between cache replacement algorithms used in the scalable asynchronous cache consistency scheme. (c2006)

    A Comparative study between cache replacement algorithms used in the scalable asynchronous cache consistency scheme. (c2006) by Turk, Lana

    Published 2006
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  6. 186
    Complexities of special matrix multiplication problems

    Complexities of special matrix multiplication problems by Takche, J.

    Published 1988
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  7. 187
    Prediction of EV Charging Behavior Using Machine Learning

    Prediction of EV Charging Behavior Using Machine Learning by Shahriar, Sakib

    Published 2021
    “…Using data-driven tools and machine learning algorithms to learn the EV charging behavior can improve scheduling algorithms. …”
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  8. 188
    Parallel implementation of clique partitioning using artificial neural networks. (c2000)

    Parallel implementation of clique partitioning using artificial neural networks. (c2000) by Hajj, Hisham

    Published 2000
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  9. 189
    Haplotype inference by pure-parsimony using revamped delayed haplotype selection. (c2011)

    Haplotype inference by pure-parsimony using revamped delayed haplotype selection. (c2011) by Abdallah, Raymond

    Published 2011
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  10. 190
    The multi-parameterized cluster editing problem

    The multi-parameterized cluster editing problem by Abu-Khzam, Faisal N.

    Published 2017
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  11. 191
    Incremental Genetic Algorithm

    Incremental Genetic Algorithm by Mansour, Nashat

    Published 2006
    “…If these problems are not small in size, it becomes costly to use a genetic algorithm to reoptimize them after each modification. …”
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  12. 192
    Label dependency modeling in Multi-Label Naïve Bayes through input space expansion

    Label dependency modeling in Multi-Label Naïve Bayes through input space expansion by PKA Chitra (21749216)

    Published 2024
    “…To accommodate the heterogeneity of the expanded input space, we refine the likelihood parameters of iMLNB using a joint density function, which is adept at handling the amalgamation of data types. We subject our enhanced iMLNB model to a rigorous empirical evaluation, utilizing six benchmark datasets. …”
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  13. 193
    Topics in graph algorithms

    Topics in graph algorithms by Abu-Khzam, Faisal Nabih

    Published 2003
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  14. 194
    Augmented arithmetic optimization algorithm using opposite-based learning and lévy flight distribution for global optimization and data clustering

    Augmented arithmetic optimization algorithm using opposite-based learning and lévy flight distribution for global optimization and data clustering by Abu Zitar, Raed

    Published 2022
    “…This paper proposes a new data clustering method using the advantages of metaheuristic (MH) optimization algorithms. …”
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  15. 195
    Minimizing using BBO and DFO methods

    Minimizing using BBO and DFO methods by El Zeghondy, Jean

    Published 2022
    “…In [1], Nour and Zeidan proposed a numerical algorithm to solve optimal control problems involving sweeping processes. …”
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  16. 196
    Information reconciliation through agent controlled graph model. (c2018)

    Information reconciliation through agent controlled graph model. (c2018) by Saba, Rita

    Published 2018
    “…Multiple models have been proposed and different techniques and data structures were used. …”
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  17. 197
    Arabic Text Classification Using Modified Artificial Bee Colony Algorithm for Sentiment Analysis: The Case of Jordanian Dialect

    Arabic Text Classification Using Modified Artificial Bee Colony Algorithm for Sentiment Analysis: The Case of Jordanian Dialect by Habeeb, Abdallah

    Published 2022
    “…The second phase, modified the Artificial Bee Colony (ABC) Algorithm, with Upper Confidence Bound (UCB) Algorithm, to promote the exploitation ability for the minimum dimension, to get the minimum number of the optimal feature, then using forward feature selection strategy by four classifiers of machine learning algorithms: (K-Nearest Neighbors (KNN), Support vector machines (SVM), Naïve-Bayes (NB), and Polynomial Neural Networks (PNN). …”
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  18. 198
    Effective solutions for the capacitated vehicle routing problem and for the split delivery vehicle routing problem with time windows. (c2013)

    Effective solutions for the capacitated vehicle routing problem and for the split delivery vehicle routing problem with time windows. (c2013) by Hilal, Nathalie

    Published 2013
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  19. 199
    On-site workshop investment problem: A novel mathematical approach and solution procedure

    On-site workshop investment problem: A novel mathematical approach and solution procedure by Nima Moradi (19418821)

    Published 2023
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  20. 200
    On the parameterized parallel complexity and the vertex cover problem

    On the parameterized parallel complexity and the vertex cover problem by Abu-Khzam, Faisal N.

    Published 2016
    “…We initiate the study of FPPT with the well-known k-vertex cover problem. In particular, we present a parallel algorithm that outperforms the best known parallel algorithm for this problem: using O(m) instead of O(n2) parallel processors, the running time improves from 4logn+O(kk) to O(k⋅log3n) , where m is the number of edges, n is the number of vertices of the input graph, and k is an upper bound of the size of the sought vertex cover. …”
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